移动机器人环境视觉图像小波稀疏压缩传感与恢复重构  

Wavelet Sparsity Based Compressive Sensing and Reconstruction for Mobile Robot Environmental Vision

作　　者：刘继忠[1] 金明亮[1] 马如远[2] 柴国钟[2] 王光辉[1,3] 

机构地区：[1]南昌大学机电工程学院,江西南昌330031 [2]浙江工业大学机械学院,浙江杭州310000 [3]滑铁卢大学系统设计工程系

出　　处：《南昌大学学报（工科版）》2013年第3期267-270,275,共5页Journal of Nanchang University(Engineering & Technology)

基　　金：国家自然科学基金资助项目(61273282);江西省教育厅自然科学基金资助项目(GJJ12005)

摘　　要：基于最新压缩传感技术理论,采用小波稀疏方法和正交匹配跟踪算法,对移动机器人常规环境视觉图像压缩传感存储与恢复重构进行了研究。结果表明:进行小波稀疏的压缩传感编码可以大大减少机器人环境视觉图像信息量,降低存储与传输代价,通过正交匹配追踪算法恢复的视觉图像,可以满足机器人常规环境视觉探测。Based on the novel compressed sampling theory, compressed sensing storage and reconstruction for environment images from robot vision were researched in the paper by the help of wavelet sparsity and orthogonal matching pursuit algorithm. Experiments of several typical environment images for sparsity, compressed storage, and reconstruction were carried out. The result showed it could reduce the amount of environment images information, and lower the cost of information storage and transmission. The reconstruction images could generally satisfy the re- quirement of robot environment exploration.

关 键 词：机器人 环境视觉 小波稀疏 图像重构 压缩传感 

分 类 号：TP274[自动化与计算机技术—检测技术与自动化装置] TP242.6[自动化与计算机技术—控制科学与工程]